Abstract:Li-ion batteries are at the core of new energy vehicle powertrains. The model-based battery management system (BMS) is the key to ensure the full play of battery performance. However,the existing BMS mainly adopts the equivalent circuit model (ECM),without considering the impact of discharge rate on available capacity. Therefore,the model will have significant terminal voltage simulation errors in different discharge rates and low state of charge (SOC) regions,which affects the accuracy of BMS. BMS cannot accurately estimate the battery discharge cut-off condition,and the estimation error of residual discharge capacity (RDC) is large,which may lead to serious consequences such as battery voltage sag and vehicle breakdown. To solve the above problems,based on the extended equivalent circuit model (EECM) considering the internal diffusion mechanism,the incremental capacity (IC) curves of discharge voltage at different rates are compared and analyzed. Nernst equation is used to construct capacity open circuit voltage curves at different discharge rates,and an improved EECM is proposed. The simulation errors of the improved EECM for terminal voltage under different current rates and dynamic conditions are smaller than traditional ECM and EECM. Improved EECM can improve the accuracy of RDC estimation and have the potential to be applied in practical BMS.

Abstract:Virtual power plant (VPP) is an important solution for distributed energy management of power grid. VPP's participation in carbon emission trading can give full play to its environmental benefits and improve the overall income of VPP. Based on the demand for electric vehicles to participate in the certification and emission reduction market,a coordinated scheduling optimization strategy for aggregating electric vehicles through VPP to participate in the carbon market is proposed. Firstly,design a scheme for VPP to represent electric vehicles in the certification and emission reduction market,and increase VPP revenue by charging service fees. Then,analyze the carbon emission characteristics of different aggregated resources in VPP and evaluate the volatility of new energy output by scenario generation method. Finally,with the goal of maximizing VPP revenue,design an optimization model for VPP participation in the carbon market. The aggregation of electric vehicles as controllable loads and energy storage devices can increase the stability of VPP operation. Example analysis shows that aggregating multiple types of resources including electric vehicles through VPP and participating in carbon market can not only incentivize VPP to reduce the power generation of traditional thermal power units and reduce carbon emissions generated during VPP operation, but also improve the stability of VPP operation,increase VPP revenue and social benefits through the use of electric vehicles.

Abstract:Fast charging station (FCS) is an important energy supply facility for electric vehicle (EV). With the popularization and application of EV,the fast charging load is gradually rising,which has a certain impact on the operation of distribution network. However,as a demand-side response resource,fast charging load can mitigate the negative impact of EV access on distribution network operation through orderly charging control. Therefore,an EV charging guidance strategy considering user charging decision-making behavior is proposed. Firstly,considering the impact of dynamic traffic conditions,an EV mobility model is constructed by using trip chain theory to simulate user trips and characterize the spatio-temporal distribution of remaining electricity. Secondly,considering the remaining electricity,charging facilities distribution and charging service price,the user charging decision model is constructed by using regret theory,and the spatio-temporal distribution of charging load is characterized. Then,the charging service price optimization model is constructed to minimize the distribution network loss. By optimizing the charging service price of the public FCS,the space-time distribution of charging load is guided. Finally,by comparing different service price schemes,the results show that the proposed method has better guidance effect on small capacity vehicles. The larger the equivalent conversion coefficient of user time consumption,the better the effect of the proposed method on charging load guidance.

Abstract:With the widespread use of distributed photovoltaic large-scale power generation,the net load 'duck' curve has become more apparent. However,electric vehicle charging during the day is unable to fully utilize the new energy,and charging at night only adds to the already existing load peak. To address the issue of net load 'peak-to-peak' exacerbation,the charging load transfer process is facililated with the objective of minimizing the peak-valley difference of net load. To achieve this,statistical data on fast and slow charging behaviors are used to predict future charging load distribution through Monte Carlo simulations. Fast and slow charging load constraints are then established based on the network access characteristics of slow charging and the delayed charging characteristics of fast charging. Then,the load transfer rate is calculated using the gradient descent method,and the charging load price response model is constructed based on user consumption psychology. Finally,economic analysis of power grid peak shaving limits the constraint of electricity price change,and a charging guidance model is constructed with the goal of minimizing the peak-valley difference of net load. Deep reinforcement learning is used to solve the model and solution strategy. The simulation results show that the proposed model and solution strategy can effectively guide the charging load to avoid the peak period of the net load,determine a reasonable price,and reduce the peak-valley difference of the power grid.

Abstract:In order to solve the problem of difficulty in achieving individual scheduling for large-scale electric vehicles entering the grid and the existence of "dimensionality disaster" in cluster scheduling,a hierarchical and partitioned optimization operation model for active distribution network based on vehicle-to-grid(V2G) mode is established. The upper level optimization model schedules the electric vehicle agent (EVA) of electric vehicles, optimizes the charging and discharging power of EVA in each region,and serves as input for the lower level optimization model. Lower level optimization model adjusts various voltage regulation methods. In terms of optimization algorithm,a self adaptive differential evolution biogeography based optimization (SaDE-BBO) algorithm is proposed and simulated in the improved IEEE 33-node distribution system. The results show that under different charging control strategies,the coordinated interaction between V2G mode and various voltage regulation methods has significant advantages in reducing EVA operating costs in various regions,suppressing load fluctuations,and ensuring the safe and economic operation of active distribution networks. Compared with other optimization algorithms,the SaDE-BBO algorithm has better solutions and convergence.

Abstract:Aiming at the power fluctuation problem for the randomness of the time-space transfer of electric vehicles (EV),taking into account the gender difference of car owners,different real-time travel purpose and two-way travel of car owners,the charge-discharge dispatch strategy based on the two-way travel chain for the travel randomness of EV is proposed. Firstly,the two-way travel chain of EV is established by considering the actual travel process of car owners. Secondly, the real-time travel probability model is given by considering the gender differences of the male and female owners travel. Then,the dispatch model is set up by reducing the power fluctuation as the objective function according to the real-time travel demand of the owner and the real-time state of charge (SOC) of EV. Finally,the charge and discharge of EV are dispatched according to the established model,and the simulation if given by analyzing the cars in a area of 280 square meters. The simulation results show that the two-way travel model is closer to the actual travel law of owners,and the dispatch strategy based on the dispatched model of the two-way travel chain can better restrain the power fluctuation.

Abstract:The distributed parameter model of the transmission line is a necessary premise for accurately analysing the harmonic instability of the wind farm. However,when the model is used for harmonic instability analysis,it causes difficulties in solving the zero and pole distributions of the transcendental equation of the system. Given this,the impedance model of the wind farm considering the line distribution parameters is established and verified. Next,a method based on Pade approximation to solve the zero and pole distributions of the transcendental equation is proposed. The exponential function is approximated to the rational fraction only by selecting the order of the rational fraction,without fitting coefficients. Further,the influence of different transmission line models on the harmonic instability under different line lengths and grid strengths is analyzed. Finally,the effectiveness of the proposed method is verified by the simulation case. The results show that the effect of distribution parameters cannot be ignored,otherwise,it may lead to the inaccurate analysis of stability and deviation or even omission of harmonic amplification points in the high-frequency band. The proposed method can not only accurately evaluate the stability of the system,but also analyze the harmonic amplification points.

Abstract:To investigate the effects of time-harmonic current introduced by inverter on loss characteristics of fractional-slot concentrated-winding permanent magnet synchronous machine (FSCW-PMSM),a method is proposed to analyze the harmonic characteristics of losses of the machine in inverter and FSCW-PMSM combined system. Firstly,the time- and space-harmonic characteristics of losses considering time-harmonic current are theoretically analyzed. Then,a 10-pole and 12-slot PMSM with three-phase double-layer winding is taken as an example. The field-circuit co-simulation model of the prototype and space vector pulse width modulation (SVPWM) inverter is established,the harmonic characteristics of losses are calculated under constant torque and constant power speed control,and the causes of each harmonic loss are revealed. The results show that rotor harmonic losses are caused by fundamental current with sub-harmonic,iZ±p slot harmonics,and (f_c±4f)/f,(f_c±2f)/f time-harmonic current with p,Z±p space harmonics. Stator core harmonic losses are caused by fundamental magnetic field,magnet harmonic excitation magnetic field and (f_c±4f)/f,(f_c±2f)/f time-harmonic current. The conclusions can be applied to the FSCW-PMSMs with other pole-slot combinations. Finally,the proposed method is validated by experiment results.

Abstract:Flexible DC technology has revolutionary significance in flexibly solving the problem of high proportion of new energy consumption. Due to the vulnerability of high-ratio power electronic equipment and the difficulty in extracting fault information,traditional line protection schemes can no longer be reliably adapted to the flexible DC transmission system. A rapid protection scheme for flexible DC transmission lines based on voltage traveling wave steepness is proposed in this paper. By analyzing the transient characteristics of DC line faults,and utilizing the differences in the steepness and polarity of fault voltage traveling waves on both sides of the current-limiting reactor, the range of effective transient information extraction is increased,and the fault identification inside or outside the region is realized. The faults are classificated by utilizing the significant difference in the degree of voltage traveling wave variation between the faulty and sound poles. Lightning interference is considered and a rapid identification method is proposed by using its initial change characteristics. Finally,the performance of the protection scheme under various influencing factors is verified by simulation,which can identify faults quickly and reliably and has good sensitivity and anti-interference ability.

Abstract:False data injection (FDI) attack is one of the attacks that can seriously affect the operation of power systems. Some studies have focused on the cyber-attack methods of AC-DC hybrid systems. However,few studies pay their efforts on the optimization of FDI attack on AC-DC hybrid systems. Therefore,an FDI attack strategy optimization method for AC-DC hybrid systems is proposed in the paper. Firstly,a two-layer optimization model with the objective of maximizing the loss of FDI attacks is established. In the upper model,the attacker launches FDI attack on the measuring system to find the optimal attack strategy to maximize the economic loss of the power system. The lower layer model calculates the maximum economic loss under a FDI attack with the objective of minimizing the generator output adjustment and load shedding，considering the security constraint of AD-DC hybrid system and the risk of commutate failure of DC converter station. Then,the two-layer optimization model is solved by the genetic algorithm to generate the optimal attack strategy. Finally,the improved IEEE 14-bus system is taken as an example to verify the effectiveness of the model. Simulation results show that the attack strategy optimized by the proposed method can effectively improve the cost of security constrained economic dispatch (SCED).

Abstract:For the analysis of the coupling characteristics of the power system frequency dynamic and power angle oscillation,the mechanism of the two-machine system under disturbances is derived in this paper, and the mechanism of the multi-machine system is obtained based on the extended equal area criterion (EEAC). A quantitative assessment index is proposed based on the Pearson coefficient,which quantified the coupling according to the characteristics of frequency dynamics and power angle oscillation. The influence of power angle oscillation on the frequency dynamic indices is analyzed,and the coupling degrees of between the power angle oscillation and different frequency dynamic indices are assessed quantitatively. The results of the mechanism analysis and case study verify the proposed quantitative indices and show the coupling characteristics of the power system frequency dynamic and power angle oscillation,which provided guidance for optimal frequency and power angle control.

Abstract:With the improvement of the requirements for the safe operation of distribution network lines,the harmonics injected by distributed power generation make the existing line selection methods ineffective,and the fault line selection method with a single criterion becomes more and more difficult to meet the line selection work after the single-phase ground fault occurs in the complex distribution network system. Therefore,a single-phase grounding fault joint line selection for resonant grounding system considering the injection harmonics of distributed power sources is proposed. In view of the characteristics of different phases and periodic changes of transient zero-sequence current of fault lines and sound lines after a single-phase grounding fault occurs in the resonant grounding system,the transient zero-sequence current is calculated by multi-scale cross-sample entropy according to the difference in low-frequency period. Then,according to the high-frequency phase difference,the weighted transient energy method and the synchronous squeeze wavelet transform are used to calculate the reconstruction error of the high-frequency transient zero-sequence current. In addition,the weighted transient energy method is used to control the calculation amount and determine the fault line through three criteria:multi-scale cross-sample entropy,weighted transient energy and reconstruction error. The experimental results show that the joint line selection method is less affected by different fault conditions and this method has high accuracy and strong anti-interference.

Abstract:The change in the operating state of the compressor will cause the variety of working conditions in gas network,affecting the steady-state power flow of electric-gas-heat integrated energy system. In order to calculate the gas network power flow of the comprehensive energy system under different operation states,the sub-networks and energy coupling links of integrated energy system are modeled respectively. Considering five working modes and two driving modes of the compressors,based on Newton-Raphson method,an integrated power flow calculation method which reserves the pipelines of compressors is proposed and an equivalent solution method which separates the pipelines of compressors is developed for gas network with multiple compressors under different operation states. The power flow of integrated energy system is calculated by distributed algorithm. The accuracy and effectiveness of the proposed integrated power flow calculation method are verified through two examples,which remedies the disadvantages of existing power flow calculation models of gas network that cannot deal with complex working conditions in gas network and lack convergence and universality. Then the impacts of the change in compressor operation states on power flow of integrated energy system are revealed.

Abstract:As an important resource on the demand side,air-conditioning load can flexibly participate in the power system and promote new energy consumption. In the process of air-conditioning load scheduling,there are differences in thermal comfort requirements and scheduling potential among different users. How to satisfy the user differentiated thermal comfort and tap their scheduling potential is a difficult problem to consider. In response to the above problem,the thermal comfort model is firstly introduced to comprehensively quantify the user's thermal comfort experience. Secondly,according to the human parameters in the thermal comfort model,the K-means clustering method is used to divide the user groups with different characteristics of thermal tolerance. On this basis,the air-conditioning direct load control strategy based on user differentiated thermal comfort is proposed and validated by simulation. The example analysis shows that,compared with the traditional strategy,the strategy proposed in this paper fully taps the scheduling potential of different user groups on the basis of completing the consumption task,and guarantees the thermal comfort of them.

Abstract:A huge amount of historical data has been generated during the operation of wind farms,and the improvement of data quality is the prerequisite work for achieving high-efficient and intelligent maintenance of wind farms. Therefore,the distribution characteristics and formation mechanism of wind power data in wind farms are analyzed,and a variance change rate criterion and quartile combined method to identify abnormal wind power data is proposed. Firstly,the original wind power curve is preprocessed by physical rules,and the obviously abnormal data is eliminated. Then,the abnormal power data points of the accumulation type of the wind power curve are identified and cleaned by the wind power variance change rate criterion method,and the threshold value of the criterion is automatically obtained through the box plot. After that,the quartile method is used to identify and clean the discrete abnormal data points. Finally,the feasibility of the proposed algorithm is verified by an example. The results show that the proposed algorithm has the advantages of easy implementation,high efficiency,and strong universality. The anomaly recognition performance of the proposed method is superior to the local outlier factor (LOF) or Thompson tau-quartile algorithms,and the value of its time consumption is 9.6 s or 0.49 s lower than that of the LOF or Thompson tau-quartile algorithm,respectively. The universality of the proposed algorithm has been verified at 5 wind farms in different locations.

Abstract:With the development of smart grid and the continuous introduction of communication equipments into cyber physical system (CPS),CPS is confronted with a new attack mode with more destructive—coordinated cyber physical attack (CCPA). CCPA is not only hidden but also threatening,which is easy to cause cascading failures. Firstly,from the perspective of the attacker,a multi-stage coordinated cyber-physical topology attack model is proposed. The single-stage physical attack first trips a transmission line,and the two-stage cyber attack is used to mask the outage signal of the disconnected line in the physical layer and then create a new fake tripped line in the cyber layer. Secondly,combined with deep reinforcement learning (DRL) theory,the method for determining the minimum attack resources based on deep Q-network (DQN) is proposed. Then,the specific model and solution method for the attacker are given,taking the maximization of the physical attack effect in the upper layer and minimization of the attack cost in the lower layer into consideration. Finally,the IEEE 30-bus system is taken as an example to verify the effectiveness of the proposed multi-stage attack model. The simulation results demonstrate that the multi-stage coordinated cyber-physical topology attack is more hidden and effective than the single attack,and the damage to the power grid is greater,which provides a reference for the defender against such attacks.

Abstract:The wide distributed energy has been the focus of power market. However,the traditional power trading platform cannot meet the high efficiency,flexibility,security and reliability requirements of the large-scale distributed energy transactions. To resolve the contradiction between high information processing complexity and the requirements of safe and fast transactions,a distributed energy trading system architecture and its overall design scheme based on cloud-edge collaboration and block chain is proposed. First of all,the system architecture of cloud computing and edge computing collaboration combined with two-layer blockchain is designed to realize transaction decentralization by using blockchain technology. It improves the autonomy and efficiency of transactions,and enhancs the processing capacity of massive data and the expansion capacity of the transaction system by using cloud edge collaboration. Then,a distributed energy trading mechanism is designed based on two-way bidding and prediction compensation, and the core consensus algorithm of blockchain is further analyzed. The delegated proof of stake (DPoS) is used as a highly efficient and reliable consensus algorithm of the trading system to realize efficient and reliable transactions of large-scale distributed energy,thus promoting distributed energy to participate in power grid regulation and improving the stable operation level of power grid. Finally,the applicability and superiority of the proposed system to large-scale distributed energy trading are verified by application example.

Abstract:In order to ensure the accurate application of the data collected by the phasor measurement unit (PMU),it is necessary to eliminate the abnormal data in its measured values. The existing PMU abnormal data identification algorithm has the disadvantages of high algorithm complexity,difficulty in online updating,difficulty in the calibration of multi-source data,and difficulty in application relying on multi-source data. In this paper,an abnormal data identification framework is proposed based on the PMU event data and abnormal data model and the definition of PMU abnormal data identification information entropy. On the basis of the framework,a PMU abnormal data identification algorithm is proposed based on the balanced iterative reducing and clustering using hierarchies (BIRCH) algorithm. The proposed algorithm is implemented,and an algorithm experiment is carried out for the PMU dataset of a substation. The experimental results show that the proposed algorithm has better accuracy and real-time performance than one-class support vector machine (OCSVM) algorithm and gap statistic algorithm.

Abstract:Dead-beat predictive current control (DPCC) has great potential in the field of motor control due to its fast response. However,it suffers from low robustness due to its sensitivity to parameter variations. In this paper,a DPCC of permanent magnet synchronous motors (PMSM) combined with parameter adaptation is proposed to enhance the robustness of the dead-beat control under parameter misalignment. Firstly,the basic principles of dead-beat current control are introduced. Then,the influence of parameter errors on the control loop of dead-beat current control under imprecise motor parameters is analyzed. To address the issue of imprecise motor parameters,a predictive current control method combined with a parameter-adaptive algorithm is proposed. The motor parameters are identified online,and the parameters of the predictive current controller are modified in real-time to achieve parameter correction. Finally,comparative simulations and performance evaluations are conducted to validate the effectiveness of the proposed method. The results show that the robustness of the current control system is significantly improved,resulting in better control performance when applying the method proposed in this paper.

Abstract:Flexible alternative current transmission systems (FACTS) devices such as the hybrid unified power flow controller (HUPFC) can adjust the line power flow and effectively increase the transmission capacity of the transmission network. To solve the problems caused by the mechanical on-load tap changer (OLTC) used in the traditional HUPFC,a fast electromagnetic HUPFC based on full-power electronic OLTC is proposed in this paper. Firstly,the operation characteristics of HUPFC are studied,and a method to suppress the overvoltage generated in the switching process is proposed. At the same time,a tap selection strategy with the least switching times is realized by using the asymmetric stage voltage Sen transformer with the existence of degrees of freedom in the synthesis method of operating points,and the detailed steps from power flow instruction change to switching voltage regulation are given. Finally,the 220 kV double-loop circuit simulation model is built in Simulink,and the power flow regulation process and results of the fast electromagnetic HUPFC are compared with those of the traditional HUPFC. The results show that the full-power electronic switch has more advantages in response speed and reducing the power fluctuation in the adjustment process than mechanical OLTC,and the feasibility of the fast electromagnetic HUPFC is verified.

Abstract:Modular multilevel matrix converter (M3C) is a new topology of AC-AC power converter,which has very broad application in low frequency transmission system,high-power asynchronous motor speed regulation and low offshore wind power transmission. Due to the power coupling effect of the two frequencies,the capacitive voltage of M3C bridge arms is prone to instability when the grid voltage is asymmetric. Firstly,the arm power of M3C under unbalanced input conditions is calculated,and the power distribution law among the arms of two different power balance method is summarized. On this basis,the influence of low-frequency circulating currents on the arm power is analyzed. Under the premise of ensuring the balance of input and output power of the system,a capacitor voltage balance control strategy based on the construction of circulating currents is proposed,which avoids the introduction of negative sequence current on the grid side. Under unbalanced conditions,the capacitor voltage can be quickly balanced by the capacitor voltage closed-loop control and direct power compensation strategy. The constructed low-frequency circulating currents only flow inside the converter,and will not affect the decoupling operation of M3C input and output sides. The effectiveness of the proposed control strategy is verified by a 220 kV,400 MW M3C system implemented in MATLAB.

Abstract:Panel-type radiator plays an important role in the heat dissipation of oil-immersed transformers. To study the influence of structural parameters of panel-type radiator on its heat dissipation performance,the multi-variable design matrix is designed by using the Box-Behnken design (BBD) method. These three key parameters (the height of the panel-type radiator, the number of weld passes,and the difference of the weld pass height) are used as independent variables,and the heat dissipation and flow resistance are the response values. STAR-CCM+ is used for numerical simulation of the model and corresponding response results are obtained. Based on the variance analysis of heat dissipation and flow resistance of the model,a quadratic regression model is obtained to analyze the interaction effects of the height of the radiator and the number of passes on heat dissipation and flow resistance. Finally,the desirability approach is used to optimize the parameters of the dispersion and determine the optimal structural parameters. The results show that the predicted values and simulation results are distributed around the regression line. The error between the predicted and simulation results is within 10%,which meets the requirements of engineering design. The increase in the height of panel-type radiator and the number of weld passes leads to an increase in heat dissipation and flow resistance,but the sensitivity of heat dissipation and flow resistance to panel-type radiator height is higher than the number of weld passes. The panel-type radiator has the best heat dissipation performance when the values of the panel-type height, the number of weld passes,and the difference of weld passes height are 2 483 mm,6,and 60 mm respectively.

Abstract:With the increase in ambient temperature around the world in summer,the working environment of cable joints is deteriorating. Based on the finite element method,a simulation model for temperature analysis in a 10 kV three-core cable and the joints is established. The temperature distribution is analyzed under different ambient temperatures and different currents. Firstly,the temperature rise experiments are carried out to obtain a steady temperature on the surface of the cable joint,which verifies the accuracy of the simulation model. Then,the relationships between the surface temperature and the current of the high voltage current carrying conductor of the joint under different ambient temperatures are fitted. The ultimate safe current carrying capacity of the joint under the different ambient temperatures can be calculated by using these related functions. The results show that the increase of ambient temperature has little effect on the temperature distribution trend of the high voltage conductor surface of the joint,which also meets this rule on the outer surface of the outer sheath. The relation of the surface temperature on the high voltage conductor of the joint to the current is approximately a quadratic function. When the current amplitude is 480 A and the ambient temperature is 75 ℃, the highest temperatures on the surface of the high-voltage current-carrying conductor and the outer surface of the outer sheath are 1.57 and 1.69 times higher respectively than at an ambient temperature of 30 ℃. When the ambient temperature exceeds 55 ℃,the continuous allowable current carrying capacity specified in the national standard can make the high voltage copper conductor of the joint exceed the maximum permitted operating temperature of 90 ℃. Considering the continuous increase in summer ambient temperature since 2020,the continuous allowable current carrying capacity of the intermediate joint of 10 kV copper conductor three-core cross-linked polyethylene insulated cables in the GB needs to be improved and perfected.

Abstract:In order to evaluate the insulation condition of oil-immersed transformers effectively,a weight allocation method considering expert experience and degradation state is proposed in this paper. Firstly,a hierarchical structure for insulation condition evaluation is built based on dissolved gas in oil,ambient temperature and defect information,and subjective weights is assigned to each index based on expert experience. Then,the method of combined weight is adopted to introduce entropy weight into the weight allocation of index layer,thus weights of the index layer are dynamically adjusted to reflect the differences in the individual operation process while retaining expert experience for the criterion layer. Furthermore,the transformer insulation state is subdivided into five states from common four to realize more accurate perception of insulation state. Finally,case study of four 500 kV transformers shows that the method proposed can effectively identify normal transformers and discriminate abnormal transformers compared with the method based only on objective or subjective weight,which verifies the rationality of the method.

Abstract:During the process of switching-off shunt reactors with vacuum circuit breakers (VCBs),reignition overvoltages (ROVs) may occur due to current chopping and arc reignition,which may damage the insulation of main power equipment and endanger the stability and safety of the power grid. In order to analyze the transient characteristics and potential hazards,in this research an accurate three-phase arc reignition model of the VCB,is developed in PSCAD/EMTDC with considering the arc characteristics of the two contacts of VCBs. Then the system simulation model of a 220 kV substation is further established. Then two factors are considered to analyze their effects on ROVs,including the opening angle and the dielectric insulation recovery velocity of VCBs. Subsequently,two types of coordinated protection schemes are proposed,including a surge arrester (SA) and a RC snubber,and a SA and a ferrite magnetic ring (FMR). Then their suppression performance is compared with that of the SA,RC snubber and FMR installed alone,and the mitigation performance of different installation positions is also investigated. Finally,the effectiveness of the proposed coordinated protection schemes for ROVs is validated. The research results of this paper can provide theoretical support for practical applications of switching-off shunt reactors and the overvoltage suppression.

Abstract:A systematic solution for millisecond-level power control in photovoltaic (PV) power stations is proposed to enable the new energy power output to rapid response to the balance of active and reactive power demands in the system. Firstly,utilizing the fast power exchange capability of the PV inverter,real-time voltage and current are collected at the grid connection point of the PV power station,and the frequency and voltage changes are monitored to calculate the active power output of the PV power station based on primary frequency regulation parameters. Based on this,the PV inverters are controlled in a group via a high-speed interconnection communication network to achieve primary frequency regulation capability. In terms of reactive power control,an intelligent multi-state sequence discrimination algorithm is employed to calculate the impedance of the grid connection point of the PV power station to the power system in real time. Based on the voltage fluctuation at the grid connection point,the PV inverters are controlled in a group to achieve dynamic reactive power response,thereby achieving rapid power control of the PV power station. The proposed control system has been piloted at the Jinhu PV power station in Huai'an,and the on-site test data shows that the control system can achieve a primary frequency regulation response time of less than 0.15 s and a dynamic reactive power response time of less than 30 ms,thereby verifying the effectiveness and feasibility of the control system.

Abstract:Vibration signals associated with on-load tap-changer (OLTC) gear switching is closely related to its mechanical state. Based on the high-dimensional phase point spatial distribution of the vibration signal of OLTC,the vibration signals at multiple positions of OLTC are represented by tensor quantization to capture as rich as possible the mechanical status information of OLTC. Then,the third order tensor in the phase space is decomposed into Tucker tensor to obtain the core tensor,and a discriminative model of OLTC mechanical fault based on convolutional neural network is established. Taking the vibration signal of a certain CM type OLTC as an example for analysis,the results show that the phase space core tensor information of the vibration signal of OLTC is comprehensive and less redundant when the OLTC acts. The mechanical fault diagnosis model based on the convolutional neural network has good performance,with an accuracy rate of more than 95%,which can provide a reference for fault identification and condition maintenance of OLTC.